Digital Twin based on Process Models and Plant Data for Blast Furnace Performance Prediction
10X SAVINGS IN ENGINEERING TIME FOR BLAST FURNACE WITH DIGITAL TWIN
Testimonial
“We worked with the Intelimek team to implement a web-based comprehensive Digital Twin for Blast Furnace. Their ability to understand the domain, and expertise in deploying such advanced systems has significantly enhanced our ability to analyze and optimize blast furnace performance.“
– Sr. Technologist, Intelligent Systems and Mathematical Modelling, One IT, Tata Steel
Scenario
Just 1% efficiency improvement in Blast Furnace operations can lead to significant savings. Bast Furnace performance analysis and prediction is challenging. Blast furnace performance is highly dependent upon the dynamic process conditions that influence the gas flow inside the furnace and dictate the efficiency of the heat transfer and reduction processes. It is difficult to measure these parameters due to high temperatures, pressure, and hostile atmosphere.
Solution
- Process model is developed for burden distribution using the sensors data
- CFD model is developed to analyze the iron extraction process considering complexities due to heat & mass transfer, and multi-phase conditions
- Automated workflow is developed connecting the process data from central system and the models that can be used even by the operations people for performance insights
- CFD Model provides insights about various internal processes taking place and distribution of various physical parameters
Key Benefits
- All integrated solution deployed on private cloud server
- Wider access and consistent usage
- Centrally managed data
- Daily comparison of Predicted versus Actual enables improvement